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Pandas Series: min() function

Minimum values in Pandas requested axis

The min() function is used to get the minimum of the values for the requested axis.

If you want the index of the minimum, use idxmin. This is the equivalent of the numpy.ndarray method argmin.

Syntax:

Series.min(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs)
Pandas Series minimum image

Parameters:

Name Description Type/Default Value Required / Optional
axis Axis for the function to be applied on. {index (0)} Required
skipna Exclude NA/null values when computing the result. bool
Default Value: True
Required
level If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. int or level name
Default Value: None
Required
numeric_only Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series. bool
Default Value: None
Required
**kwargs Additional keyword arguments to be passed to the function. Required

Returns: scalar or Series (if level specified)

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
    ['warm', 'warm', 'cold', 'cold'],
    ['fox', 'lion', 'snake', 'spider']],
    names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s

Output:

blooded  animal
warm     fox       4
         lion      4
cold     snake     0
         spider    8
Name: legs, dtype: int64
Pandas Series minimum image

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
    ['warm', 'warm', 'cold', 'cold'],
    ['fox', 'lion', 'snake', 'spider']],
    names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s.min()

Output:

0

Example - Min using level names, as well as indices:

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
    ['warm', 'warm', 'cold', 'cold'],
    ['fox', 'lion', 'snake', 'spider']],
    names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s.min(level='blooded')

Output:

blooded
warm    4
cold    0
Name: legs, dtype: int64

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
    ['warm', 'warm', 'cold', 'cold'],
    ['fox', 'lion', 'snake', 'spider']],
    names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s.min(level=0)

Output:

blooded
warm    4
cold    0
Name: legs, dtype: int64

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https://w3resource.com/pandas/series/series-min.php